The present invention relates generally to a method of controlling the operation of an electronic computer and more particularly to a method of maintaining consistency of cached data in a computer database system of the kind in which objects are copied from a database into a cache for ready access by a client application.
Many modern computer systems include databases that must be accessible to a number of users more or less simultaneously. Typically, not all of these users are at the same location. For example, an airline reservation system includes a central computer that contains flight schedules, passenger reservations, seat assignments, fares and the like. This information must be available on demand to many hundreds of reservation clerks and travel agents at numerous locations throughout the nation.
Another example is a bank computer system. The computer contains account balances and other information respecting the bank's customers. Tellers in various branches of the bank must have access to the information in the computer to process deposits, withdrawals and other transactions. In addition, more and more bank customers are conducting their own banking transactions themselves by using automatic teller machines ("ATMs") that are located not only in banks but in airports, shopping centers, and other public places, and by using personal computers located in their homes.
Still another example is a local area network ("LAN") that interconnects a plurality of workers (e.g., attorneys, engineers, secretaries) in an office or other working environment. A computer contains word processor files (such as standard documents, legal briefs, research reports, correspondence and the like), design projects, electronic messages, and other data access to which may be required at any time by one or more of the workers.
It will be apparent that when several users are simultaneously working with a database two or more of them may attempt to alter the same item of data at the same time. For example, a teller may attempt to process a customer's withdrawal or deposit in a branch office of a bank at the same time as an account clerk in the main office is debiting checks and service charges to the same customer's account. A conflict between these transactions can result in erroneous data being entered into the database. The prevention of such conflicts is known as concurrency control.
More specifically, in the context of a database system the term "transaction" is defined as "a logical unit of work." Date, C. J., An Introduction to Database Systems, 4th Ed., Vol. 1, pub. Addison-Wesley, 1986, page 413. Typically, a logical unit of work is a sequence of steps that culminates with a "commit request", that is, an attempt permanently to alter an item of data in the database. "Transactions" are sometimes referred to in the literature by such terms as "client transactions" and "user transactions"; they will be referred to herein as "working transactions" to distinguish them from the client applications which generate them and from human users of the database system.
Many database management systems use "locks" for concurrency control. In a widely used two-phase lock approach to concurrency control, the server grants a working transaction a share ("S") lock on an "object" in the database when the transaction wishes to prevent the object from being changed for a limited period of time. In physical terms, an S lock comprises a control signal, an entry in a computer register, or the like that prevents the computer from altering the locked object. More than one transaction can have an S lock on an object at the same time.
The server grants a working transaction an exclusive ("X") lock on an object when the transaction is about to alter the object. If a given transaction has an X lock on an object, no other transaction can acquire either an S or an X lock on the object. This prevents the other transaction from attempting to read or alter the item during the time the given transaction is engaged in altering the item.
To prevent any loss of generality, the term "object" as used herein should be understood as referring either to a data object (a set of data items and relations among those data items) in the context of an object-oriented database or to any item of data in the context of some other kind of database.
When a working transaction requests a lock on an object, the request is either granted, delayed or denied by the server. If the request is granted, the transaction is said to have "acquired" the lock. If the request is delayed, the transaction waits for further word from the server, and if the request is denied the transaction usually aborts.
Under some circumstances, the granting of a requested lock must occur immediately because of the status of some condition of the system at the time the request is made. For convenience, this is referred to herein as "getting" a lock as opposed to "acquiring" a lock which implies that the server grants the lock only after determining that the lock can properly be granted.
For more information on database locking system generally, see Date, An Introduction to Database Systems (cited above), Ch. 18 and the references cited therein.
A common paradigm for providing shared access to computer database such as the examples mentioned above is a client-server system. A client-server system includes a centrally located main computer (the "server") in which a database is stored and a plurality of satellite computers (the "clients") which are linked to the main computer by some form of electronic communication system and which use portions of the database as needed.
A server usually comprises a computer, a database, memory for storing the database, and database management software. The memory typically consists of some combination of random-access memory ("RAM") and magnetic media such as tapes and disks, but some computer systems may use optical media and other storage devices. Depending on the requirements of the system, the server might be anything from a desktop personal computer with a hard disk and commercially available database software to a large mainframe computer with multiple tape drives and specially designed database software.
A client is typically a personal computer such as a Hewlett-Packard Vectra, a workstation such as a Hewlett-Packard 9000 series, or some other kind of computer terminal such as a bank ATM machine. The client has its own memory which is usually smaller than the server memory. Most clients are remote from the server, but in some systems a client may be collocated with the server and may even use a portion of the same physical memory device as used by the server instead of having its own.
Each client has one or more "applications" such as word processors, spread sheets, electronic mail, computer-aided design ("CAD") programs, and database interface software that communicate with the server to obtain information from the database, to update information in the database and to add new information to the database. Some of these applications may be under the control of a human operator and others may run automatically or under the control of another application.
An electronic communication system which may comprise, for example, commercial telephone lines and dedicated circuits carries messages between the clients and the server. Sending large numbers of messages back and forth is costly, not only in terms of the expense of operating the communication system but also in terms of time and computer resources. Therefore it is desirable to minimize the number of messages that flow between the clients and the server.
One way to reduce the number of messages is to copy a portion of the data from the server's memory into a "cache" in the client's memory. This cached data is then used by the client as needed without having to send a message to the server each time an item of data must be referred to.
A cache and the memory in which it is stored are typically physically located in a client which as noted above is remote from the server. However, in some installations one or more caches may be stored in a different portion of the same physical memory device as is used by the server to store the database. Thus, although a client cache is always distinct from the main database and is usually physically located in a separate memory structure that may be thousands of miles away, the two may be physically adjacent in a single memory device.
There must be a protocol between the client and the server to ensure that the data in the cache remains consistent with the data in the main server database. In this sense, the client cache may be viewed as active data since updates to the server database should trigger a cache refresh operation so that the updated information is also put into the cache.
An "active" database allows a client application to be informed of changes made by other applications to an "active" portion of the data in the main server database. In the context of a client-server system, this has meant that all updates to the server database must be monitored by the database management system to determine whether the updates affect any active data associated with any other application. When updates affect any active data, the affected clients must be informed that a change has occurred. Thus, every transaction incurs heavy overhead to support a detection and notification service that often is not needed to benefit the transaction.
It will be apparent that as the number of clients increases, the overhead required to keep the various client caches current also increases. For example, in a large system such as an airline reservation system or a bank computer system there may be hundreds of clients caching data at locations many hundreds of miles from the server. Even in a LAN system in a single office building there may be a hundred or more clients caching data in personal computers and workstations. The overhead required to keep all these caches current can substantially degrade performance of the system.
There have been various attempts to reduce this cache consistency overhead and thereby improve system performance. In one such approach the primary motivation for maintaining multiple copies of data was to improve system reliability and availability; in that environment, all copies of the data are assumed persistent and extra overhead is incurred to keep the multiple copies up to date. Bernstein, P. A., and N. Goodman, "An Algorithm for Concurrency Control and Recovery in Replicated Distributed Databases," ACM Transactions on Database Systems. Vol. 9, No. 4,December 1984; Gifford, D. K., "Weighted Voting for Replicated Data," Proceedings of the 7th Symposium on Operating Systems Principles, December 1979.
Another approach emphasizes an efficient mechanism for refreshing a snapshot of data (a snapshot may be considered a kind of cache) after an update to the database by means of a refresh algorithm for views over a single base table. Lindsay, B., L. Haas, C. Mohan, H. Pirahesh and P. Wilms, "A Snapshot Differential Refresh Algorithm," Proceedings of the 1986 SIGMOD Conference, Washington D.C., June 1986. To detect view updates, a base table must be augmented with a timestamp and link field for each tuple. An algorithm for arbitrary select-project-join views is described in Blakeley, J. A., P. -A. Larson and F. W. Tompa, "Efficiently Updating Materialized Views," Proceedings of the 1986 SIGMOD Conference, Washington D.C., June 1986. Each update transaction has a side effect of building additional sets of tuples to add or remove from each affected view.
A system that supports read-only caching for workstations accessing a central database is described in Gladney, H. M., "Data Replicas in Distribued Information Services," ACM Transactions on Database Systems, Vol. 14, No. 1, March 1989. This system requires changes to the database management system to timestamp base data.
Optimistic concurrency control is a system that does not use locks. Instead, transactions proceed unhindered until commit time, at which time conflicts must be resolved. Kung, H. T., and J. T. Robinson, "On Optimistic Methods for Concurrency Control,", ACM Transactions on Database Systems, Vol. 6, No. 2, June 1981. This system is generally considered to be more suitable for non-distributed database systems than for client-server systems.
Timestamping methods that do not use locks have also been proposed. In these methods, each update of a data object is timestamped. A commit request includes both a read/write set and the time at which its transaction started. The server then checks this time against the time stamps of all other working sets for any conflicts. Bernstein, P. A., and N. Goodman, "Timestamp-Based Algorithms for Concurrency Control in Distributed Database Systems," Proceedings of the 6th International Conference on Very Large Data Bases, October 1980. This system was developed in an effort to avoid the overhead of a locking system.
Other approaches involve cooperating transactions and active databases with real time requirements. Fernandez, M. F., and S. B. Zdonik, "Transaction Groups: A Model for Controlling Cooperative Transactions," Proceedings of the Workshop on Persistent Object Systems: Their Design, Implementation and Use, Newcastle, Australia, January 1989; Risch, T., "Monitoring Database Objects", Proceedings of the 15th International Conference on Very Large Data Bases, Amsterdam, 1989, also described in copending U.S. patent application Ser. No. 07/286,556, filed Dec. 19, 1988 and assigned to the same assignee as the present application; and Rosenthal, A., S. Chakravarthy, B. Blaustein and J. Blakely, "Situation Monitoring for Active Databases," Proceedings of the 15th International Conference on Very Large Data Bases, Amsterdam, 1989. A system of nested transactions has also been proposed. Moss, J. E. B., Nested Transactions: An Approach to Reliable Distributed Computing, PhD thesis, Massachusetts Institute of Technology, April 1981. However, none of these approaches has adequately solved the problem of maintaining the consistency of cached data.
It will be apparent from the foregoing that there remains a need for an efficient way to maintain the consistency of cached data in a client-server database system.